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DBMS > Amazon DynamoDB vs. Drizzle vs. GridDB vs. Sphinx

System Properties Comparison Amazon DynamoDB vs. Drizzle vs. GridDB vs. Sphinx

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Editorial information provided by DB-Engines
NameAmazon DynamoDB  Xexclude from comparisonDrizzle  Xexclude from comparisonGridDB  Xexclude from comparisonSphinx  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionHosted, scalable database service by Amazon with the data stored in Amazons cloudMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Scalable in-memory time series database optimized for IoT and Big DataOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument store
Key-value store
Relational DBMSTime Series DBMSSearch engine
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score77.72
Rank#16  Overall
#2  Document stores
#2  Key-value stores
Score2.00
Rank#137  Overall
#11  Time Series DBMS
Score6.06
Rank#61  Overall
#6  Search engines
Websiteaws.amazon.com/­dynamodbgriddb.netsphinxsearch.com
Technical documentationdocs.aws.amazon.com/­dynamodbdocs.griddb.netsphinxsearch.com/­docs
DeveloperAmazonDrizzle project, originally started by Brian AkerToshiba CorporationSphinx Technologies Inc.
Initial release2012200820132001
Current release7.2.4, September 20125.1, August 20223.5.1, February 2023
License infoCommercial or Open Sourcecommercial infofree tier for a limited amount of database operationsOpen Source infoGNU GPLOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++C++
Server operating systemshostedFreeBSD
Linux
OS X
LinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyesyes infonumerical, string, blob, geometry, boolean, timestampno
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.no
Secondary indexesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLnoyes infowith proprietary extensionsSQL92, SQL-like TQL (Toshiba Query Language)SQL-like query language (SphinxQL)
APIs and other access methodsRESTful HTTP APIJDBCJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Proprietary protocol
Supported programming languages.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby
C
C++
Java
PHP
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnononono
Triggersyes infoby integration with AWS Lambdano infohooks for callbacks inside the server can be used.yesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
Source-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)noConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Immediate consistency within container, eventual consistency across containers
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoACID across one or more tables within a single AWS account and regionACIDACID at container levelno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Pluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users can be defined per databaseno
More information provided by the system vendor
Amazon DynamoDBDrizzleGridDBSphinx
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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More resources
Amazon DynamoDBDrizzleGridDBSphinx
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